NanoString Technologies, a leading provider of life science tools for discovery and translational research, and Visiopharm, a leader in AI-driven digital pathology software, have announced a collaboration to accelerate the discovery of novel biomarkers and drug targets using the latest spatial imaging and machine learning technologies.
Together, NanoString and Visiopharm are developing integrated workflows leveraging the multiplexing capability of the GeoMx Digital Spatial Profiler (DSP) and the AI-driven image analysis capabilities of Visiopharm. NanoString’s new cloud informatics platform, the AtoMx Spatial Informatics Platform, will enhance the integration by providing scalable computing power with worldwide access.
Integrating Visiopharm’s Oncotopix Discovery software into the GeoMx DSP workflow will enhance and simplify sample processing for translational research applications. Researchers can leverage Visiopharm’s AI algorithms to analyse four-colour fluorescent images generated on GeoMx (pictured) as well as associated images using hematoxylin and eosin (H&E) staining, to better understand the number and type of cells within DSP profiling regions. The combination of these technologies is expected to accelerate biomarker discovery and validation with in-situ whole transcriptome and high-plex protein analysis.
Additionally, NanoString and Visiopharm will maintain file format compatibility that enables researchers to analyse GeoMx DSP whole-slide images with the Visiopharm software, providing access to a rich toolset for pathologic and spatial analysis including cell counts, phenotype mapping, distance measures, and more, which can be used to enhance and validate the high-plex spatial molecular data.
“Visiopharm is committed to transforming pathology through AI-based tissue mining, and this collaboration will combine the power of 20 years of expertise in pathology image analysis with high-plex spatial molecular analyses,” said Louise Armstrong, Chief Commercial Officer, Visiopharm. “Spatial biology is one of the fastest growing areas of research, and this collaboration will enable a deeper understanding of the spatial high-plex and whole-transcriptome data that GeoMx delivers.”
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